CASS: Towards Building a Social-Support Chatbot for Online Health Community

• URL: http://arxiv.org/abs/2101.01583v3
• Date: Thu, 4 Feb 2021 08:01:03 GMT
• Title: CASS: Towards Building a Social-Support Chatbot for Online Health Community
• Authors: Liuping Wang and Dakuo Wang and Feng Tian and Zhenhui Peng and Xiangmin Fan and Zhan Zhang and Shuai Ma and Mo Yu and Xiaojuan Ma and Hongan Wang
• Abstract summary: The CASS architecture is based on advanced neural network algorithms. It can handle new inputs from users and generate a variety of responses to them. With a follow-up field experiment, CASS is proven useful in supporting individual members who seek emotional support.
• Score: 67.45813419121603
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Chatbots systems, despite their popularity in today's HCI and CSCW research, fall short for one of the two reasons: 1) many of the systems use a rule-based dialog flow, thus they can only respond to a limited number of pre-defined inputs with pre-scripted responses; or 2) they are designed with a focus on single-user scenarios, thus it is unclear how these systems may affect other users or the community. In this paper, we develop a generalizable chatbot architecture (CASS) to provide social support for community members in an online health community. The CASS architecture is based on advanced neural network algorithms, thus it can handle new inputs from users and generate a variety of responses to them. CASS is also generalizable as it can be easily migrate to other online communities. With a follow-up field experiment, CASS is proven useful in supporting individual members who seek emotional support. Our work also contributes to fill the research gap on how a chatbot may influence the whole community's engagement.

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